Assessment of Drag Prediction Techniques for a Flying Vehicle Based on Radar-Tracked Data

Abstract As far as the aerodynamic characterization of a flying vehicle is concerned, flight testing probably most accurate approach it perfectly resembles real environment. Flight data are obtained by tracking via radars if modifying design not recommended/attainable. In open literature, different techniques used to analyze radar data; key issue computational demands each technique and quality resulting characteristics. this paper, three considered namely, Least-Square (LS), Maximum-Likelihood Estimation (MLE), Stepwise Regression (SR), with focus on prediction drag coefficient case study vehicle. Features for addressed based brief previous published data. A new variant MLE method proposed physical segmentation available dataset. Predicted point-mass trajectories compared own comprehensive test assess in concern. It concluded that Stepwise-regression outperforms large dataset, while more feasible considering lack The yields basic one.